Abstract Optical brain imaging allows the noninvasive mapping of human brain activity in a quiet and magnet-free environment. This technology is particularly important for patients who have implanted medical devices, such as cochlear implants, that rule out magnetic resonance imaging. Being able to map brain activity in patients with implanted medical devices is critical because it allows us to understand the complex balance between neural networks in individuals that support successful behavior, and to diagnose where breakdowns in activity are problematic. Adult listeners with cochlear implants are a unique group in which to investigate task-evoked neural activity: They have typically adapted to auditory deprivation for a period of years of profound hearing loss, followed by some degree of hearing restoration following implantation. Following increased auditory input due to cochlear implantation, the degree to which individual listeners are able to successfully recognize speech, especially in the presence of background noise, is extremely variable. Previous attempts to explain this variability in the context of underlying patterns of brain activity have been unsuccessful, in large part because the technical challenges associated with neuroimaging in the presence of an implanted medical device have prevented whole-brain imaging of neural responses to speech. The goal of our research is to bring methodological improvements to bear in optical neuroimaging that will allow us to use high-density diffuse optical tomography (HD-DOT) to effectively image single-subject responses to spoken language. We will validate atlas-based spatial normalization, necessary in patients with medical implants because they do not have MRI images available to aid the localization process. We will also develop improved head models and denoising algorithms that will improve the optical imaging signal-to-noise ratio. Finally, we will implement a novel story comprehension paradigm to map receptive language areas in individual participants, including measures of test-retest reliability, which we will then translate to patients with cochlear implants. Our long-term research plan is to understand the neural systems that support speech recognition in listeners with cochlear implants and to use knowledge about these systems to improve behavioral outcomes.